Identification of candidate genes for milk production traits by RNA sequencing on bovine liver at different lactation stages

• Main Authors: Qian Li, Ruobing Liang, Yan Li, Yanxia Gao, Qiufeng Li, Dongxiao Sun, Jianguo Li
• Format: Article
• Language: English
• Published: BMC 2020-07-01
• Series: BMC Genetics
• Subjects: RNA-sequencing; Liver; Candidate gene; Milk production traits; Dairy cattle
• Online Access: http://link.springer.com/article/10.1186/s12863-020-00882-y

Abstract Background RNA-sequencing was performed to explore the bovine liver transcriptomes of Holstein cows to detect potential functional genes related to lactation and milk composition traits in dairy cattle. The bovine transcriptomes of the nine liver samples from three Holstein cows during dry period (50-d prepartum), early lactation (10-d postpartum), and peak of lactation (60-d postpartum) were sequenced using the Illumina HiSeq 2500 platform. Results A total of 204, 147 and 81 differentially expressed genes (DEGs, p < 0.05, false discovery rate q < 0.05) were detected in early lactation vs. dry period, peak of lactation vs. dry period, and peak of lactation vs. early lactation comparison groups, respectively. Gene ontology and KEGG pathway analysis showed that these DEGs were significantly enriched in specific biological processes related to metabolic and biosynthetic and signaling pathways of PPAR, AMPK and p53 (p < 0.05). Ten genes were identified as promising candidates affecting milk yield, milk protein and fat traits in dairy cattle by using an integrated analysis of differential gene expression, previously reported quantitative trait loci (QTL), data from genome-wide association studies (GWAS), and biological function information. These genes were APOC2, PPP1R3B, PKLR, ODC1, DUSP1, LMNA, GALE, ANGPTL4, LPIN1 and CDKN1A. Conclusion This study explored the complexity of the liver transcriptome across three lactation periods in dairy cattle by performing RNA sequencing. Integrated analysis of DEGs and reported QTL and GWAS data allowed us to find ten key candidate genes influencing milk production traits.